Empirical evidence of habits and patterns in public transport use

Summary

Demand for public transport systems is determined by high-level strategic decisions (home and work location choices), habits (preferred routes and modes) and real-time responses to changing conditions (weather, special events, incidents). The day-to-day variation in system utilisation encompasses variability in all of these aspects and makes it difficult for system operators to provide information or service changes that improve system performance. Increasing availability of data (such as transit smart card data) supports more nuanced investigations into the factors that influence public transport demand.

Supervisor(s)

Dr Emily Moylan

Research Location

Civil Engineering

Program Type

Masters/PHD

Synopsis

The project will use transit smart card data to explore travel behaviour patterns in public transport networks. Passenger demand and choices are impacted by habits and strategies for dealing with change as well as real-time responses to conditions. Disaggregate travel data provides an opportunity to isolate how these forces impact traveller behaviour and how system operators can respond. The goal is to find evidence of the interplay between typical behaviours and variability in demand on the public transport system.

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Keywords

transport, public transport, Transportation, transit, data science, traveller behaviour, performance measurement, Modelling

Opportunity ID

The opportunity ID for this research opportunity is: 2429

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